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Articles 1 - 30 of 69
Full-Text Articles in Engineering
Understanding The Impact Of Microplastic Contamination On Soil Quality And Eco-Toxicological Risks In Horticulture: A Comprehensive Review, N. P. Gayathri, Geena Prasad, Vaishna Prabhakaran, Vishnu Priya
Understanding The Impact Of Microplastic Contamination On Soil Quality And Eco-Toxicological Risks In Horticulture: A Comprehensive Review, N. P. Gayathri, Geena Prasad, Vaishna Prabhakaran, Vishnu Priya
Research outputs 2022 to 2026
The horticulture sector, essential for global food production, confronts significant challenges with prevalent pollutants, mainly microplastics. The presence of microplastics in the food chain has induced physiological stress and a multifactorial food safety concern. The complexity of the problem, arising from intricate interactions among microplastics, organisms, and ecosystems, poses a substantial challenge to food safety, necessitating an immediate strategic perspective due to the associated risks to human health and eco-toxicology. Significant knowledge gaps persist regarding their impact on terrestrial ecosystems, especially in horticulture. This study addresses the urgent need to comprehend the implications of microplastics on soil health, eco-toxicological risks, …
Microplastics Fouling Mitigation In Forward Osmosis Membranes By The Molecular Assembly Of Sulfobetaine Zwitterion, Javad Farahbakhsh, Mitra Golgoli, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar
Microplastics Fouling Mitigation In Forward Osmosis Membranes By The Molecular Assembly Of Sulfobetaine Zwitterion, Javad Farahbakhsh, Mitra Golgoli, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar
Research outputs 2022 to 2026
Forward osmosis (FO) membranes have potential for the efficient water and wastewater treatment applications. However, their development has faced significant challenges due to their fouling propensity. In this study, FO membranes modified with sulfobetaine zwitterions (i.e., [2-(Methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl) ammonium hydroxide) were fabricated and used for the first time to address microplastic (MP) fouling issue. Water flux, reverse salt flux (RSF), fouling, and flux recovery were evaluated for the membranes loaded with different quantities of the zwitterions ranging from 0.25 % to 2 %. The developed membranes were tested over 49 h with feed solutions containing polyethylene MPs and bovine serum albumin …
Maximizing Charge Dynamics In Znin2s4/Cn Van Der Waals Heterojunction For Optimal Hydrogen Production From Photoreforming Of Glucose, Jinqiang Zhang, Xinyuan Xu, Lei Shi, Huayang Zhang, Shaobin Wang, Hongqi Sun
Maximizing Charge Dynamics In Znin2s4/Cn Van Der Waals Heterojunction For Optimal Hydrogen Production From Photoreforming Of Glucose, Jinqiang Zhang, Xinyuan Xu, Lei Shi, Huayang Zhang, Shaobin Wang, Hongqi Sun
Research outputs 2022 to 2026
Biomass photoreforming stands out as a promising avenue for green hydrogen, leveraging solar energy for the generation and transformation of clean and renewable energy resources. The pursuit of efficient photocatalysts is motivated by the unsatisfied hydrogen evolution performance arising from the complex and stubborn structure of biomass. Herein, we loaded 2-dimensional (2D) ZnIn2S4 onto 2D carbon nitride nanosheets, resulting in the formation of Van der Waals (VDW) heterojunctions (ZIS/CN). Band structure and morphology of CN were rationally tailored through precursor engineering to effectively magnify interfacial internal electric field and minimize diffusion pathway within the VDW heterostructure, realizing optimal charge dynamics …
Mhair: A Dataset Of Audio-Image Representations For Multimodal Human Actions, Muhammad Bilal Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Mhair: A Dataset Of Audio-Image Representations For Multimodal Human Actions, Muhammad Bilal Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Research outputs 2022 to 2026
Audio-image representations for a multimodal human action (MHAiR) dataset contains six different image representations of the audio signals that capture the temporal dynamics of the actions in a very compact and informative way. The dataset was extracted from the audio recordings which were captured from an existing video dataset, i.e., UCF101. Each data sample captured a duration of approximately 10 s long, and the overall dataset was split into 4893 training samples and 1944 testing samples. The resulting feature sequences were then converted into images, which can be used for human action recognition and other related tasks. These images can …
Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Research outputs 2022 to 2026
Multimodal Human Action Recognition (MHAR) is an important research topic in computer vision and event recognition fields. In this work, we address the problem of MHAR by developing a novel audio-image and video fusion-based deep learning framework that we call Multimodal Audio-Image and Video Action Recognizer (MAiVAR). We extract temporal information using image representations of audio signals and spatial information from video modality with the help of Convolutional Neutral Networks (CNN)-based feature extractors and fuse these features to recognize respective action classes. We apply a high-level weights assignment algorithm for improving audio-visual interaction and convergence. This proposed fusion-based framework utilizes …
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia
Research outputs 2022 to 2026
Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …
Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer
Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer
Research outputs 2022 to 2026
Hydrogen is a clean fuel that can potentially completely decarbonize the energy supply chain and mitigate global warming. Hydrogen – a highly volatile gas – however, needs to be separated from CO2 during H2 production, and also from cushion gas in H2 geo-storage projects; in addition, large-scale H2 storage is a key obstacle. We thus tested and chemically upgraded common sub-bituminous coal as a material for H2-CO2 separation and H2 storage. The coal adsorbed significant amounts of H2 and CO2 and demonstrated an excellent H2-CO2 separation efficiency if chemically modified. The work presented here thus provides fundamental data required for …
On The Effect Of Emotion Identification From Limited Translated Text Samples Using Computational Intelligence, Madiha Tahir, Zahid Halim, Muhmmad Waqas, Shanshan Tu
On The Effect Of Emotion Identification From Limited Translated Text Samples Using Computational Intelligence, Madiha Tahir, Zahid Halim, Muhmmad Waqas, Shanshan Tu
Research outputs 2022 to 2026
Emotion identification from text data has recently gained focus of the research community. This has multiple utilities in an assortment of domains. Many times, the original text is written in a different language and the end-user translates it to her native language using online utilities. Therefore, this paper presents a framework to detect emotions on translated text data in four different languages. The source language is English, whereas the four target languages include Chinese, French, German, and Spanish. Computational intelligence (CI) techniques are applied to extract features, dimensionality reduction, and classification of data into five basic classes of emotions. Results …
Wastewater Treatment Plants: The Missing Link In Global One-Health Surveillance And Management Of Antibiotic Resistance, Abdolmajid Gholizadeh, Mehdi Khiadani, Maryam Foroughi, Hadi Alizade Siuki, Hadi Mehrfar
Wastewater Treatment Plants: The Missing Link In Global One-Health Surveillance And Management Of Antibiotic Resistance, Abdolmajid Gholizadeh, Mehdi Khiadani, Maryam Foroughi, Hadi Alizade Siuki, Hadi Mehrfar
Research outputs 2022 to 2026
Introduction: As a global public health crisis, antibiotic resistance (AR) should be monitored and managed under the One-Health concept according to the World Health Organization (WHO), considering the interconnection between humans, animals, and the environment. But this approach often remains focused on human health and rarely on the environment and its compartments, especially wastewater as the main AR receptor. Wastewater treatment plants (WWTPs) not only are not designed for reliving AR but also provide appropriate conditions for enhancing AR through different mechanisms. Methods: By reviewing the research-based statistics on the inclusion of WWTPs in the One-Health/AR program crisis, this paper …
Study On The Performance Of Solar Cells Cooled With Heatsink And Nanofluid Added With Aluminum Nanoparticle, Rouhollah Salehi, Ahmad Jahanbakhshi, Jong B. Ooi, Abbas Rohani, Mahmood R. Golzarian
Study On The Performance Of Solar Cells Cooled With Heatsink And Nanofluid Added With Aluminum Nanoparticle, Rouhollah Salehi, Ahmad Jahanbakhshi, Jong B. Ooi, Abbas Rohani, Mahmood R. Golzarian
Research outputs 2022 to 2026
The cooling of photovoltaic (PV) panels based on nanofluids is one of the emerging cooling methods to improve the efficiency of PV panels. In this study, the effects of aluminum nanoparticles on the cooling performance and conversion efficiency of PV panels were investigated experimentally. The surface temperature, output power, and efficiency of the PV panels were assessed in Mashhad, Iran on a sunny winter day in November 2020 under ambient temperatures between 10 and 17 °C. Experimental results indicated that the nanofluid with aluminum nanoparticle improved the solar panel efficiency and solar PV panel's output power by an average of …
Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman
Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman
Research outputs 2022 to 2026
Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, …
Structure-Aware Image Translation-Based Long Future Prediction For Enhancement Of Ground Robotic Vehicle Teleoperation, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed M. S. Islam
Structure-Aware Image Translation-Based Long Future Prediction For Enhancement Of Ground Robotic Vehicle Teleoperation, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed M. S. Islam
Research outputs 2022 to 2026
Predicting future frames through image-to-image translation and using these synthetically generated frames for high-speed ground vehicle teleoperation is a new concept to address latency and enhance operational performance. In the immediate previous work, the image quality of the predicted frames was low and a lot of scene detail was lost. To preserve the structural details of objects and improve overall image quality in the predicted frames, several novel ideas are proposed herein. A filter has been designed to remove noise from dense optical flow components resulting from frame rate inconsistencies. The Pix2Pix base network has been modified and a structure-aware …
Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Research outputs 2022 to 2026
We present PyMAiVAR, a versatile toolbox that encompasses the generation of image representations for audio data including Wave plots, Spectral Centroids, Spectral Roll Offs, Mel Frequency Cepstral Coefficients (MFCC), MFCC Feature Scaling, and Chromagrams. This wide-ranging toolkit generates rich audio-image representations, playing a pivotal role in reshaping human action recognition. By fully exploiting audio data's latent potential, PyMAiVAR stands as a significant advancement in the field. The package is implemented in Python and can be used across different operating systems.
Ultrasonic Study Of Water Adsorbed In Nanoporous Glasses, Jason Ogbebor, John J. Valenza, Peter I. Ravikovitch, Ashoka Karunarathne, Giovanni Muraro, Maxim Lebedev, Boris Gurevich, Alexei F. Khalizov, Gennady Y. Gor
Ultrasonic Study Of Water Adsorbed In Nanoporous Glasses, Jason Ogbebor, John J. Valenza, Peter I. Ravikovitch, Ashoka Karunarathne, Giovanni Muraro, Maxim Lebedev, Boris Gurevich, Alexei F. Khalizov, Gennady Y. Gor
Research outputs 2022 to 2026
Thermodynamic properties of fluids confined in nanopores differ from those observed in the bulk. To investigate the effect of nanoconfinement on water compressibility, we perform water sorption experiments on two nanoporous glass samples while concomitantly measuring the speed of longitudinal and shear ultrasonic waves in these samples. These measurements yield the longitudinal and shear moduli of the water-laden nanoporous glass as a function of relative humidity that we utilize in the Gassmann theory to infer the bulk modulus of the confined water. This analysis shows that the bulk modulus (inverse of compressibility) of confined water is noticeably higher than that …
Design And Concept Of Renewable Energy Driven Auto-Detectable Railway Level Crossing Systems In Bangladesh, Iftekharuzzaman Iftekharuzzaman, Susmita Ghosh, Mohammad K. Basher, Mohammad A. Islam, Narottam Das, Mohammad Nur-E-Alam
Design And Concept Of Renewable Energy Driven Auto-Detectable Railway Level Crossing Systems In Bangladesh, Iftekharuzzaman Iftekharuzzaman, Susmita Ghosh, Mohammad K. Basher, Mohammad A. Islam, Narottam Das, Mohammad Nur-E-Alam
Research outputs 2022 to 2026
Bangladesh’s railway system mostly uses typical manual railway crossing techniques or boom gates through its 2955.53 km rail route all over the country. Accidents frequently happen at railway crossings due to the lack of quickly operating gate systems, and to fewer safety measures at the railway crossing as well. Currently, there are very few automatic railway crossing systems available (without obstacle detectors). Additionally, all of them are dependent on the national power grid, without a backup plan for any emergency cases. Bangladesh is still running a bit behind in generating enough power for its consumption; hence, it is not possible …
Physical Layer Authenticated Image Encryption For Iot Network Based On Biometric Chaotic Signature For Mpfrft Ofdm System, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek Hassan
Physical Layer Authenticated Image Encryption For Iot Network Based On Biometric Chaotic Signature For Mpfrft Ofdm System, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek Hassan
Research outputs 2022 to 2026
In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the multi-parameter fractional Fourier transform–Orthogonal frequency division multiplexing (MP-FrFT-OFDM) is suggested for secure image transmission over the IoT network. In addition, a new robust multi-cascaded chaotic modular fractional sine map (MCC-MF sine map) is designed and analyzed. Also, a new dynamic chaotic biometric signature (DCBS) generator based on combining the biometric signature and the proposed MCC-MF sine map random chaotic sequence output is also designed. The final output of the proposed DCBS generator is used as a dynamic secret key for the MPFrFT OFDM system in which …
Photocatalytic Reforming Of Lignocellulose: A Review, Xinyuan Xu, Lei Shi, Shu Zhang, Zhimin Ao, Jinqiang Zhang, Shaobin Wang, Hongqi Sun
Photocatalytic Reforming Of Lignocellulose: A Review, Xinyuan Xu, Lei Shi, Shu Zhang, Zhimin Ao, Jinqiang Zhang, Shaobin Wang, Hongqi Sun
Research outputs 2022 to 2026
Biomass has been considered as a promising energy resource to combat the exhaustion of fossil fuels, as it is renewable, sustainable, and clean. Photocatalytic reforming is a novel technology to utilize solar energy for upgrading biomass in relatively mild conditions. This process efficiently reforms and recasts biomass into hydrogen and/or valuable chemicals. To date, lignocellulose, including cellulose, hemicellulose and lignin, has attracted extensive studies in facile photocatalytic valorisation. This review summarizes and analyzes the most recent research advances on photoreforming of lignocellulose to provide insights for future research, with a particular emphasis on the reformation of lignin because of its …
A Provable Secure And Efficient Authentication Framework For Smart Manufacturing Industry, Muhammad Hammad, Akhtar Badshah, Ghulam Abbas, Hisham Alasmary, Muhammad Waqas, Wasim A. Khan
A Provable Secure And Efficient Authentication Framework For Smart Manufacturing Industry, Muhammad Hammad, Akhtar Badshah, Ghulam Abbas, Hisham Alasmary, Muhammad Waqas, Wasim A. Khan
Research outputs 2022 to 2026
Smart manufacturing is transforming the manufacturing industry by enhancing productivity and quality, driving growth in the global economy. The Internet of Things (IoT) has played a crucial role in realizing Industry 4.0, where machines can communicate and interact in real-time. Despite these advancements, security remains a major challenge in developing and deploying smart manufacturing. As cyber-attacks become more prevalent, researchers are making security a top priority. Although IoT and Industrial IoT (IIoT) are used to establish smart industries, these systems remain vulnerable to various types of attacks. To address these security issues, numerous authentication methods have been proposed. However, many …
A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung
A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung
Research outputs 2022 to 2026
The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …
Long Future Frame Prediction Using Optical Flow Informed Deep Neural Networks For Enhancement Of Robotic Teleoperation In High Latency Environments, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed M. S. Islam
Long Future Frame Prediction Using Optical Flow Informed Deep Neural Networks For Enhancement Of Robotic Teleoperation In High Latency Environments, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed M. S. Islam
Research outputs 2022 to 2026
High latency in teleoperation has a significant negative impact on operator performance. While deep learning has revolutionized many domains recently, it has not previously been applied to teleoperation enhancement. We propose a novel approach to predict video frames deep into the future using neural networks informed by synthetically generated optical flow information. This can be employed in teleoperated robotic systems that rely on video feeds for operator situational awareness. We have used the image-to-image translation technique as a basis for the prediction of future frames. The Pix2Pix conditional generative adversarial network (cGAN) has been selected as a base network. Optical …
Comparative Static And Dynamic Analyses Of Solvents For Removal Of Asphaltene And Wax Deposits Above- And Below-Surface At An Iranian Carbonate Oil Field, Milad Norouzpour, Amin Azdarpour, Rafael M. Santos, Ali Esfandiarian, Moein Nabipour, Erfan Mohammadian, Abbas K. Manshad, Alireza Keshavarz
Comparative Static And Dynamic Analyses Of Solvents For Removal Of Asphaltene And Wax Deposits Above- And Below-Surface At An Iranian Carbonate Oil Field, Milad Norouzpour, Amin Azdarpour, Rafael M. Santos, Ali Esfandiarian, Moein Nabipour, Erfan Mohammadian, Abbas K. Manshad, Alireza Keshavarz
Research outputs 2022 to 2026
During production from oil wells, the deposition of asphaltene and wax at surface facilities and porous media is one of the major operational challenges. The crude oil production rate is significantly reduced due to asphaltene deposition inside the reservoir. In addition, the deposition of these solids inside the surface facilities is costly to oil companies. In this study, the efficiency of different solvents in dissolving asphaltene and wax was investigated through static and dynamic tests. The analysis of solid deposits from the surface choke of one of the Iranian carbonate oil fields showed that they consisted of 41.3 wt % …
Plant Protein-Based Nanocomposite Films: A Review On The Used Nanomaterials, Characteristics, And Food Packaging Applications, Shima Jafarzadeh, Mehrdad Forough, Sajed Amjadi, Vahid J. Javan Kouzegaran, Hadi Almasi, Farhad Garavand, Masoumeh Zargar
Plant Protein-Based Nanocomposite Films: A Review On The Used Nanomaterials, Characteristics, And Food Packaging Applications, Shima Jafarzadeh, Mehrdad Forough, Sajed Amjadi, Vahid J. Javan Kouzegaran, Hadi Almasi, Farhad Garavand, Masoumeh Zargar
Research outputs 2022 to 2026
Consumer demands to utilize environmentally friendly packaging have led researchers to develop packaging materials from naturally derived resources. In recent years, plant protein-based films as a replacement for synthetic plastics have attracted the attention of the global food packaging industry due to their biodegradability and unique properties. Biopolymer-based films need a filler to show improved packaging properties. One of the latest strategies introduced to food packaging technology is the production of nanocomposite films which are multiphase materials containing a filler with at least one dimension less than 100 nm. This review provides the recent findings on plant-based protein films as …
Design, Development, And Characterization Of Highly Efficient Colored Photovoltaic Module For Sustainable Buildings Applications, Mohammad Khairul Basher, Mohammad Nur-E-Alam, Momtazur Rahman, Steven Hinckley, Kamal Alameh
Design, Development, And Characterization Of Highly Efficient Colored Photovoltaic Module For Sustainable Buildings Applications, Mohammad Khairul Basher, Mohammad Nur-E-Alam, Momtazur Rahman, Steven Hinckley, Kamal Alameh
Research outputs 2022 to 2026
The building integrated photovoltaic (BIPV) system is one of the contributors which has enormous potential to reach the goal of net-zero energy buildings (NZEB) that significantly reduce the use of fossil fuels that contribute to global warming. However, the limitations of the visual and aesthetic appearance of current BIPV systems make this aspiration unlikely. This study investigates the limitations of the single-color-based PV modules that are dull in appearance and have low photo-conversion efficiency (PCE). In order to solve this issue, we designed, developed, and characterized micro-patterned-based multicolored photovoltaic (MPCPV) modules which are applicable to net-zero building and development. Our …
Towards A Digital Twin For Characterising Natural Source Zone Depletion: A Feasibility Study Based On The Bemidji Site, Kaveh Sookhak Lari, Greg B. Davis, John L. Rayner
Towards A Digital Twin For Characterising Natural Source Zone Depletion: A Feasibility Study Based On The Bemidji Site, Kaveh Sookhak Lari, Greg B. Davis, John L. Rayner
Research outputs 2022 to 2026
Natural source zone depletion (NSZD) of light non-aqueous phase liquids (LNAPLs) may be a valid long-term management option at petroleum impacted sites. However, its future long-term reliability needs to be established. NSZD includes partitioning, biotic and abiotic degradation of LNAPL components plus multiphase fluid dynamics in the subsurface. Over time, LNAPL components are depleted and those partitioning to various phases change, as do those available for biodegradation. To accommodate these processes and predict trends and NSZD over decades to centuries, for the first time, we incorporated a multi-phase multi-component multi-microbe non-isothermal approach to representatively simulate NSZD at field scale. To …
Effect Of Humic Acid On Co2-Wettability In Sandstone Formation, Mujahid Ali, Faisal Ur Rahman Awan, Muhammad Ali, Ahmed Al-Yaseri, Muhammad Arif, Mónica Sánchez-Román, Alireza Keshavarz, Stefan Iglauer
Effect Of Humic Acid On Co2-Wettability In Sandstone Formation, Mujahid Ali, Faisal Ur Rahman Awan, Muhammad Ali, Ahmed Al-Yaseri, Muhammad Arif, Mónica Sánchez-Román, Alireza Keshavarz, Stefan Iglauer
Research outputs 2014 to 2021
© 2020 Elsevier Inc. Hypothesis: Millions of tons of CO2 are stored in CO2 geological storage (CGS) formations (depleted oil reservoirs and deep saline aquifers) every year. These CGS formations naturally contain small concentrations of water-soluble organic components in particular humic acid (HA), which may drastically affect the rock wettability - a significant factor determining storage capacities and containment security. Hence, it is essential to characterise the effect of humic acid concentration on CO2-wettability and its associated impact on storage capacity. Experimental: To achieve this, we measured advancing and receding contact angles at reservoir conditions using the pendant drop tilted …
Fabrication Of Black Silicon Via Metal-Assisted Chemical Etching—A Review, Mohammad Yasir Arafat, Mohammad Aminul Islam, Ahmad W. B. Mahmood, Fairuz Abdullah, Mohammad Nur-E-Alam, Tiong Sieh Kiong, Nowshad Amin
Fabrication Of Black Silicon Via Metal-Assisted Chemical Etching—A Review, Mohammad Yasir Arafat, Mohammad Aminul Islam, Ahmad W. B. Mahmood, Fairuz Abdullah, Mohammad Nur-E-Alam, Tiong Sieh Kiong, Nowshad Amin
Research outputs 2014 to 2021
The metal-assisted chemical etching (MACE) technique is commonly employed for texturing the wafer surfaces when fabricating black silicon (BSi) solar cells and is considered to be a potential technique to improve the efficiency of traditional Si-based solar cells. This article aims to review the MACE technique along with its mechanism for Ag-, Cu- and Ni-assisted etching. Primarily, several essential aspects of the fabrication of BSi are discussed, including chemical reaction, etching direction, mass transfer, and the overall etching process of the MACE method. Thereafter, three metal catalysts (Ag, Cu, and Ni) are critically analyzed to identify their roles in producing …
Prediction Of Mean Wave Overtopping At Simple Sloped Breakwaters Using Kernel-Based Methods, Shabnam Hosseinzadeh, Amir Etemad-Shahidi, Ali Koosheh
Prediction Of Mean Wave Overtopping At Simple Sloped Breakwaters Using Kernel-Based Methods, Shabnam Hosseinzadeh, Amir Etemad-Shahidi, Ali Koosheh
Research outputs 2014 to 2021
The accurate prediction of the mean wave overtopping rate at breakwaters is vital for a safe design. Hence, providing a robust tool as a preliminary estimator can be useful for practitioners. Recently, soft computing tools such as artificial neural networks (ANN) have been developed as alternatives to traditional overtopping formulae. The goal of this paper is to assess the capabilities of two kernel-based methods, namely Gaussian process regression (GPR) and support vector regression for the prediction of mean wave overtopping rate at sloped breakwaters. An extensive dataset taken from the EurOtop database, including rubble mound structures with permeable core, straight …
Sub-Micron Moulding Topological Mass Transport Regimes In Angled Vortex Fluidic Flow, Thaar M. D. Alharbi, Matt Jellicoe, Xuan Luo, Kasturi Vimalanathan, Ibrahim K. Alsulami, Bediea S. Al Harbi, Aghil Igder, Fayed A. J. Alrashaidi, Xianjue Chen, Keith A. Stubbs, Justin M. Chalker, Wei Zhang, Ramiz A. Boulos, Darryl B. Jones, Jamie S. Quinton, Colin L. Raston
Sub-Micron Moulding Topological Mass Transport Regimes In Angled Vortex Fluidic Flow, Thaar M. D. Alharbi, Matt Jellicoe, Xuan Luo, Kasturi Vimalanathan, Ibrahim K. Alsulami, Bediea S. Al Harbi, Aghil Igder, Fayed A. J. Alrashaidi, Xianjue Chen, Keith A. Stubbs, Justin M. Chalker, Wei Zhang, Ramiz A. Boulos, Darryl B. Jones, Jamie S. Quinton, Colin L. Raston
Research outputs 2014 to 2021
Shear stress in dynamic thin films, as in vortex fluidics, can be harnessed for generating non-equilibrium conditions, but the nature of the fluid flow is not understood. A rapidly rotating inclined tube in the vortex fluidic device (VFD) imparts shear stress (mechanical energy) into a thin film of liquid, depending on the physical characteristics of the liquid and rotational speed,ω, tilt angle,θ, and diameter of the tube. Through understanding that the fluid exhibits resonance behaviours from the confining boundaries of the glass surface and the meniscus that determines the liquid film thickness, we have established specific topological mass transport regimes. …
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Research outputs 2014 to 2021
Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe …
Reversible And Irreversible Adsorption Of Bare And Hybrid Silica Nanoparticles Onto Carbonate Surface At Reservoir Condition, Zain-Ul-Abedin Arain, Sarmad Al-Anssari, Muhammad Ali, Shoaib Memon, Masood Ahmed Bhatti, Christopher Lagat, Mohammad Sarmadivaleh
Reversible And Irreversible Adsorption Of Bare And Hybrid Silica Nanoparticles Onto Carbonate Surface At Reservoir Condition, Zain-Ul-Abedin Arain, Sarmad Al-Anssari, Muhammad Ali, Shoaib Memon, Masood Ahmed Bhatti, Christopher Lagat, Mohammad Sarmadivaleh
Research outputs 2014 to 2021
© 2020 Southwest Petroleum University Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. …